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61 Network Segregation Predicts Processing Speed in the Cognitively Healthy Oldest-old
- Sara A Nolin, Mary E Faulkner, Paul Stewart, Leland Fleming, Stacy Merritt, Roxanne F Rezaei, Pradyumna K Bharadwaj, Mary Kathryn Franchetti, Daniel A Raichlen, Courtney J Jessup, Lloyd Edwards, G Alex Hishaw, Emily J Van Etten, Theodore P Trouard, David S Geldmacher, Virginia G Wadley, Noam Alperin, Eric C Porges, Adam J Woods, Ronald A Cohen, Bonnie E Levin, Tatjana Rundek, Gene E Alexander, Kristina M Visscher
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 367-368
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Objective:
Understanding the factors contributing to optimal cognitive function throughout the aging process is essential to better understand successful cognitive aging. Processing speed is an age sensitive cognitive domain that usually declines early in the aging process; however, this cognitive skill is essential for other cognitive tasks and everyday functioning. Evaluating brain network interactions in cognitively healthy older adults can help us understand how brain characteristics variations affect cognitive functioning. Functional connections among groups of brain areas give insight into the brain’s organization, and the cognitive effects of aging may relate to this large-scale organization. To follow-up on our prior work, we sought to replicate our findings regarding network segregation’s relationship with processing speed. In order to address possible influences of node location or network membership we replicated the analysis across 4 different node sets.
Participants and Methods:Data were acquired as part of a multi-center study of 85+ cognitively normal individuals, the McKnight Brain Aging Registry (MBAR). For this analysis, we included 146 community-dwelling, cognitively unimpaired older adults, ages 85-99, who had undergone structural and BOLD resting state MRI scans and a battery of neuropsychological tests. Exploratory factor analysis identified the processing speed factor of interest. We preprocessed BOLD scans using fmriprep, Ciftify, and XCPEngine algorithms. We used 4 different sets of connectivity-based parcellation: 1)MBAR data used to define nodes and Power (2011) atlas used to determine node network membership, 2) Younger adults data used to define nodes (Chan 2014) and Power (2011) atlas used to determine node network membership, 3) Older adults data from a different study (Han 2018) used to define nodes and Power (2011) atlas used to determine node network membership, and 4) MBAR data used to define nodes and MBAR data based community detection used to determine node network membership.
Segregation (balance of within-network and between-network connections) was measured within the association system and three wellcharacterized networks: Default Mode Network (DMN), Cingulo-Opercular Network (CON), and Fronto-Parietal Network (FPN). Correlation between processing speed and association system and networks was performed for all 4 node sets.
Results:We replicated prior work and found the segregation of both the cortical association system, the segregation of FPN and DMN had a consistent relationship with processing speed across all node sets (association system range of correlations: r=.294 to .342, FPN: r=.254 to .272, DMN: r=.263 to .273). Additionally, compared to parcellations created with older adults, the parcellation created based on younger individuals showed attenuated and less robust findings as those with older adults (association system r=.263, FPN r=.255, DMN r=.263).
Conclusions:This study shows that network segregation of the oldest-old brain is closely linked with processing speed and this relationship is replicable across different node sets created with varied datasets. This work adds to the growing body of knowledge about age-related dedifferentiation by demonstrating replicability and consistency of the finding that as essential cognitive skill, processing speed, is associated with differentiated functional networks even in very old individuals experiencing successful cognitive aging.
Validity of the NIH toolbox cognitive battery in a healthy oldest-old 85+ sample
- Sara A. Nolin, Hannah Cowart, Stacy Merritt, Katalina McInerney, P. K. Bharadwaj, Mary Kate Franchetti, David A. Raichlen, Cortney J. Jessup, G. Alex Hishaw, Emily J. Van Etten, Theodore P. Trouard, David S. Geldmacher, Virginia G. Wadley, Eric S. Porges, Adam J. Woods, Ron A. Cohen, Bonnie E. Levin, Tatjana Rundek, Gene E. Alexander, Kristina M. Visscher
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue 6 / July 2023
- Published online by Cambridge University Press:
- 14 October 2022, pp. 605-614
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Objective:
To evaluate the construct validity of the NIH Toolbox Cognitive Battery (NIH TB-CB) in the healthy oldest-old (85+ years old).
Method:Our sample from the McKnight Brain Aging Registry consists of 179 individuals, 85 to 99 years of age, screened for memory, neurological, and psychiatric disorders. Using previous research methods on a sample of 85 + y/o adults, we conducted confirmatory factor analyses on models of NIH TB-CB and same domain standard neuropsychological measures. We hypothesized the five-factor model (Reading, Vocabulary, Memory, Working Memory, and Executive/Speed) would have the best fit, consistent with younger populations. We assessed confirmatory and discriminant validity. We also evaluated demographic and computer use predictors of NIH TB-CB composite scores.
Results:Findings suggest the six-factor model (Vocabulary, Reading, Memory, Working Memory, Executive, and Speed) had a better fit than alternative models. NIH TB-CB tests had good convergent and discriminant validity, though tests in the executive functioning domain had high inter-correlations with other cognitive domains. Computer use was strongly associated with higher NIH TB-CB overall and fluid cognition composite scores.
Conclusion:The NIH TB-CB is a valid assessment for the oldest-old samples, with relatively weak validity in the domain of executive functioning. Computer use’s impact on composite scores could be due to the executive demands of learning to use a tablet. Strong relationships of executive function with other cognitive domains could be due to cognitive dedifferentiation. Overall, the NIH TB-CB could be useful for testing cognition in the oldest-old and the impact of aging on cognition in older populations.
Iron deficiency and high-intensity running interval training do not impact femoral or tibial bone in young female rats
- Jonathan M. Scott, Elizabeth A. Swallow, Corinne E. Metzger, Rachel Kohler, Joseph M. Wallace, Alexander J. Stacy, Matthew R. Allen, Heath G. Gasier
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- Journal:
- British Journal of Nutrition / Volume 128 / Issue 8 / 28 October 2022
- Published online by Cambridge University Press:
- 11 November 2021, pp. 1518-1525
- Print publication:
- 28 October 2022
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In the USA, as many as 20 % of recruits sustain stress fractures during basic training. In addition, approximately one-third of female recruits develop Fe deficiency upon completion of training. Fe is a cofactor in bone collagen formation and vitamin D activation, thus we hypothesised Fe deficiency may be contributing to altered bone microarchitecture and mechanics during 12-weeks of increased mechanical loading. Three-week old female Sprague Dawley rats were assigned to one of four groups: Fe-adequate sedentary, Fe-deficient sedentary, Fe-adequate exercise and Fe-deficient exercise. Exercise consisted of high-intensity treadmill running (54 min 3×/week). After 12-weeks, serum bone turnover markers, femoral geometry and microarchitecture, mechanical properties and fracture toughness and tibiae mineral composition and morphometry were measured. Fe deficiency increased the bone resorption markers C-terminal telopeptide type I collagen and tartate-resistant acid phosphatase 5b (TRAcP 5b). In exercised rats, Fe deficiency further increased bone TRAcP 5b, while in Fe-adequate rats, exercise increased the bone formation marker procollagen type I N-terminal propeptide. In the femur, exercise increased cortical thickness and maximum load. In the tibia, Fe deficiency increased the rate of bone formation, mineral apposition and Zn content. These data show that the femur and tibia structure and mechanical properties are not negatively impacted by Fe deficiency despite a decrease in tibiae Fe content and increase in serum bone resorption markers during 12-weeks of high-intensity running in young growing female rats.
Contributors
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- By Naila A. Ahmad, Dua M. Anderson, Jennifer Aunspaugh, Sabrina T. Bent, Adam Broussard, Staci Cameron, Rahul Dasgupta, Ravinder Devgun, Ofer N. Eytan, Sean H. Flack, Terry G. Fletcher, Charles James Fox, Mary Elise Fox, Scott Friedman, Louise K. Furukawa, Sonja Gennuso, Stanley M. Hall, Hani Hanna, Jacob Hummel, James E. Hunt, Ranu Jain, Joe R. Jansen, Deepa Kattail, Alan David Kaye, David J. Krodel, Gregory J. Latham, Sungeun Lee, Michael G. Levitzky, Alexander Y. Lin, Carl Lo, Hoa N. Luu, Camila Lyon, Kelly A. Machovec, Lizabeth D. Martin, Maria Matuszczak, Patrick S. McCarty, Brenda C. McClain, J. Grant McFadyen, Helen Nazareth, Dolores B. Njoku, Christina M. Pabelick, Shannon M. Peters, Amit Prabhakar, Michael Richards, Kasia Rubin, Joel A. Saltzman, Lisgelia Santana, Gabriel Sarah, Katherine Stammen, John Stork, Kim M. Strupp, Lalitha V. Sundararaman, Rosalie F. Tassone, Douglas R. Thompson, Nicole C. P. Thompson, Paul A. Tripi, Jacqueline L. Tutiven, Navyugjit Virk, Stacey Watt, B. Craig Weldon, Maria Zestus
- Edited by Alan David Kaye, Louisiana State University, Charles James Fox, Tulane University School of Medicine, Louisiana, James H. Diaz, Louisiana State University
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- Book:
- Essentials of Pediatric Anesthesiology
- Published online:
- 05 November 2014
- Print publication:
- 16 October 2014, pp ix-xii
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